AI Engineer: Production ML & Agentic Workflows

University of Texas Southwestern Medical Center

Dallas (TX)

On-site

USD 130,000 - 190,000

Full time

7 days ago

Be an early applicant

Application generator

Don’t send a generic resume — generate a resume and cover letter tailored to this exact role.

Get past ATS filters

Benefits offered by this job

Healthcare

Paid time off

Paid holidays

On-site childcare

Job summary

UT Southwestern Medical Center in Dallas is seeking an experienced software engineer to design, build, and ship production AI features within DIMS, the Innovation Hub's platform for managing faculty research tracks. You will implement agentic workflows, NLP search, retrieval pipelines, and model integrations, collaborating with product, engineering, and external collaborators.

The role emphasizes maintainable code over prototyping, with emphasis on security, compliance, observability, and

Qualifications

Bachelor's Degree in Computer Science, Engineering, or related field (or equivalent experience).
May consider additional related years of experience in lieu of degree.
Experience with agent frameworks, multi step and multi-agent orchestration, and retrieval augmented generation in production.
Familiarity with Azure AI services (Azure OpenAI Service, Azure Foundry, Azure AI Search), enterprise identity, and CI/CD pipelines.
Experience with enterprise data and security patterns, including handling of confidential or pre publication content.
Familiarity with translational research, technology transfer, or scientific literature and patent data sources.

Responsibilities

Builds and ships production AI features within DIMS, including multi step agentic workflows, natural language search, structured output, and recommendation and matching capabilities; writes and maintains the majority of the implementing code, moving agent concepts from specification to released functionality on a rapid delivery cadence rather than producing prototypes or evaluations alone.
Designs, builds, and maintains AI agents end to end, including prompt design and iteration, tool and function definitions, orchestration and routing across multi step tasks, context and memory management, and structured output contracts; develops reusable prompt, tool, and orchestration patterns so that additional agents can be stood up without rebuilding shared infrastructure; establishes prompt versioning, evaluation harnesses, regression tests, and acceptance criteria so that agent behavior is measurable, reproducible, and safe to release.
Integrates commercial and open large language models and related services into the platform through application programming interfaces, including Microsoft Azure Foundry/OpenAI Service and other institutionally approved platforms; manages model selection, versioning, cost, latency, rate limiting, and failure handling.
Develops retrieval and data pipelines that ground AI features in institutional and external sources, including faculty and laboratory datasets, invention disclosure content, and public scientific and intellectual property data sources; ensures outputs remain traceable to verifiable source material.
Partners with the product owner, software developers, and design to translate early stage commercialization workflows and stage gate criteria into working features; participates in requirements definition, technical scoping, and release planning
Implements guardrails, monitoring, and observability for accuracy, hallucination, data leakage, and cost; ensures alignment with UTSW information security, data stewardship, and compliance requirements and with intellectual property protections governing pre publication and pre patent content.
Contributes to code review, technical documentation, version control practice, and deployment automation; supports productionization and handoff of collaboratively developed prototypes into supported platform capabilities.